Title
Ontology Alignment Through Instance Negotiation: a Machine Learning Approach
Abstract
Abstract—The,Semantic Web needs methodologies,to accomplish actual commitment,on shared,ontologies among,different actors in play. In this paper, we propose a machine learning approach,to solve this issue relying on classified instance exchange and inductive reasoning. This approach is based on the idea that, whenever,two,(or more) software,entities need,to align their ontologies (which amounts, from the point of view of each entity, to add one or more new concept definitions to its own ontology), it is possible to learn the new,concept,definitions starting from shared,individuals,(i.e. individuals already,described,in terms of both ontologies, for which the entities have statements about classes and related properties); these individuals, arranged in two sets of positive and negative examples for the target definition, are used,to solve a learning problem which as solution gives the definition of the target concept,in terms,of the ontology used,for the learning,process. The method has been applied in a preliminary,prototype,for a small,multi-agent scenario (where the two,entities cited before are instantiated as two software agents). Following the prototype presentation, we report on the experimental,results we obtained and then draw,some conclusions. I. MOTIVATION The Semantic Web (SW), being an evolution of the World
Year
Venue
Keywords
2006
SWAP
inductive reasoning,ontology alignment,machine learning,semantic web,software agent
Field
DocType
Citations 
Instance-based learning,Computer science,Natural language processing,Artificial intelligence,Ontology (information science),Ontology alignment,Ontology-based data integration,Multi-task learning,Information retrieval,Process ontology,Suggested Upper Merged Ontology,Upper ontology,Machine learning
Conference
0
PageRank 
References 
Authors
0.34
9
4
Name
Order
Citations
PageRank
Ignazio Palmisano121721.16
Luigi Iannone265363.35
Domenico Redavid35115.17
Giovanni Semeraro41873222.42